Hello R community. if you’re up for some fun tinkering with a Shiny App please join me on a new project. I would love to see some collaboration in designing a Shiny Application which will help people make a decision about a healthcare provider. I have only just begun on this project but would to work with others.
This is just a quick look at the data, the roughest shiny app you’ve ever seen can be located on my shinyapps.io page
The first goal is to help people find a provider based off of City and State (or perhaps zipcode and latitude/longitude). This can take the form of a list, map, etc. I would also like people to be able to glean some information about the place they are going in comparison to the surrounding locations.
I was only able to put a an hour or so into this (and that was months ago) but have decided that it would be fun to start collaborating with anyone who is interested. Please make any pull requests and I’ll get to them!
What Type of Data Visualization Do You Choose (if any)?
Determining whether or not you need a visualization is step one. While it seems silly, this is probably something everyone (including myself) should be doing more often. A lot of times, it seems like a great way to showcase the amount of work you have been doing, but winds up being completely ineffective and could potentially harm what you’re doing. Once you determine that you actually need to visualize your data, you should have a rough idea of the options to look at. This post will explain and demonstrate some of the common types of charts and plots.
This post is dedicated to my mother – Seinfeld’s greatest fan.
Seinfeld is a classic TV sitcom. It featured four main characters surrounded by relatively normal, everyday, run of the mill scenarios. In the spirit of Seinfeld, this post will also “be about nothing.” Continue reading →
Continuing ourExplorationof the Data
After identifying the sources of crime growth, it’s time to investigate specific crime rates. This blog post addresses drug and alcohol crimes in Denver over the past few years.
This is a very simplistic view because it will only focus on trend data, which never tells the whole story. Continue reading →